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Education Major Version

MA 120 Basic Concepts of Statistics
Wiemann, Michael R.


Mission Statement: The mission of Park University, an entrepreneurial institution of learning, is to provide access to academic excellence, which will prepare learners to think critically, communicate effectively and engage in lifelong learning while serving a global community.

Vision Statement: Park University will be a renowned international leader in providing innovative educational opportunities for learners within the global society.

Course

MA 120 Basic Concepts of Statistics

Semester

S2J 2009 DN

Faculty

Wiemann, Michael R.

Title

Adjunct Faculty- Mathematics

Degrees/Certificates

M.S. - Central Missouri State University - Applied Mathematics, 2001
B.S. - Central Missouri State University - Actuarial Science and Mathematics, 1994

Office Location

Classroom of Instruction

Office Hours

By Appointment

Daytime Phone

913-323-4018

E-Mail

michael.wiemann@park.edu

mwiemann@sbcglobal.net

Semester Dates

03/16/2009 to 05/10/2009

Class Days

---R-------

Class Time

5:30 - 9:50 PM

Credit Hours

3


Textbook:

 

Required Text: Elementary Statistics, 10th Ed.
Author: Mario F. Triola
Publisher: Addison-Wesley
ISBN: 0-321-52291-5

Order text at: http://direct.mbsbooks.com/park.htm

An e-book is included with MyMathLab.  If you prefer to use it instead of the hardcopy, order the Student Access Kit only at www.mymathlab.com.  You will need your instructor's course ID code prior to ordering. 

You will also need a calculator. Check with your instructor for specific requirements on type and features. Links in the course Student Instruction Guide are provided for downloading required FREE software for the multimedia presentations of the course.

Textbooks can be purchased through the Parkville Bookstore

Additional Resources:

I would also recommend looking at the TI-83/TI-84 Resources at http://education.ti.com

McAfee Memorial Library - Online information, links, electronic databases and the Online catalog. Contact the library for further assistance via email or at 800-270-4347.
Career Counseling - The Career Development Center (CDC) provides services for all stages of career development.  The mission of the CDC is to provide the career planning tools to ensure a lifetime of career success.
Park Helpdesk - If you have forgotten your OPEN ID or Password, or need assistance with your PirateMail account, please email helpdesk@park.edu or call 800-927-3024
Resources for Current Students - A great place to look for all kinds of information http://www.park.edu/Current/.


Course Description:
A development of certain basic concepts in probability and statistics that is pertinent to most disciplines. Topics include: probability models, parameters, statistics and sampling procedures, hypothesis testing, correlation and regression. 3:0:3

Educational Philosophy:

Delivery of coursework will be done via examples, quizzes, and examinations.   

Learning Outcomes:
  Core Learning Outcomes

  1. Compute descriptive statistics for raw data as well as grouped data.
  2. Determine appropriate features of a frequency distribution.
  3. Apply Chebyshev's Theorem.
  4. Distinguish between and provide relevant descriptions of a sample and a population.
  5. Apply the rules of combinatorics.
  6. Differentiate between classical and frequency approaches to probability.
  7. Apply set-theoretic ideas to events.
  8. Apply basic rules of probability.
  9. Apply the concepts of specific discrete random variables and probability distributions.
  10. Compute probabilities of a normal distribution.
  11. Compute confidence intervals of means and percentages.
  12. Perform hypothesis tests involving one population.
  13. Compute regression and correlation of Bi-variate data.


Core Assessment:

Description of MA 120 Core Assessment


 


One problem with multiple parts for each numbered item, except for item #3, which contains four separate problems.


 


1.         Compute the mean, median, mode, and standard deviation for a sample of 8 to 12 data.


 


2.         Compute the mean and standard deviation of a grouped frequency distribution with 4 classes.


 


3.         Compute the probability of four problems from among these kinds or combinations there of:


            a.         the probability of an event based upon a two-dimensional table;


            b.         the probability of an event that involves using the addition rule;


            c.         the probability of an event that involves conditional probability;


            d.         the probability of an event that involves the use of independence of events;


            e.         the probability of an event based upon permutations and/or combinations;


            f.          the probability of an event using the multiplication rule; or


            g.         the probability of an event found by finding the probability of the complementary event.


 


4.         Compute probabilities associated with a binomial random variable associated with a practical situation. 
  
5.         Compute probabilities associated with either a standard normal probability distribution or with a non-standard normal probability distribution.

6.         Compute and interpret a confidence interval for a mean and/ or for a proportion.

Link to Class Rubric

Class Assessment:

Assessment will be done via quizzes and examinations.                       
 
 

Grading:

Three Exams @ 100 points each:                 300 points
Attendance (See below)                             100 points
Quizzes(See below)                                     100 points
Final Exam                                                    100 points

· Grades for this course will be based upon taking the total points earned divided by the total points possible. Your percentage will result in the following letter grade:

89.5% - 100.0%          A          79.5% - 89.4%            B          69.5% - 79.4%            C

59.5% - 69.4%            D          0.0% - 59.4% F

·                     Mr. Wiemann does NOT accept late homework, labs or quizzes.

·                     Your attendance is required for the full duration of class. To help motivate students towards this goal, up to 10 points will be earned for Week 1 – Week 8’s attendance in each class meeting. If a student is absent (excused or otherwise), 0 points will be earned for that class period. If a student leaves early, partial points will be awarded for that class period.

·                     Quizzes will be calculated by taking the total points earned on quizzes divided by the total points possible in quizzes and multiplying by 100. Any decimal part of an integer will be rounded to the nearest whole number (i.e. 93.5 will round to 94).

·                     Quizzes, Notes, and Solution Sets will be required to be printed by the student for use.  The student will be responsible (after Week 1) to print out any notes, solution sets, and or quizzes BEFORE class. The website will be demonstrated during the first nite of class. 

·                     Extra credit, if offered, will be at the discretion of Mr. Wiemann.

·                     All work must be shown to earn full credit on problems worked!

·                     The final exam for this course is comprehensive and required to be taken.

·                     The only dumb question is the one that is not asked. If you have an issue about the course, I would encourage you to use the methods of communication that I have (i.e. E-mail, voice mail, before or after class).

Late Submission of Course Materials:

                    Mr. Wiemann does NOT allow makeup exams. It is the student’s responsibility to take the exam on or before the scheduled date. If the score on your final exam is greater than the score earned on one of your class exams, I will replace your lowest exam score (not including quizzes) with the score earned on the final exam. For this reason, it becomes an integral part of the student’s responsibility to be there on an exam day.

Classroom Rules of Conduct:

Please refer to the Student Handbook for current policy for academic honesty. An incident of cheating consists, but not limited to, copying someone else’s work and accepting it as your own work. AT NO POINT IN THIS COURSE IS IT ACCEPTABLE TO SUBMIT SOMEONE ELSE’S WORK AS YOUR OWN. You are more than welcome to converse about how to solve a problem; however, you must submit your own work as the final submission of the assignment.
 
The first alleged incident of cheating in this course will result in a "F" being earned by the student.

Course Topic/Dates/Assignments:

This course provides an introduction to the world of statistical analysis. Each week we'll focus on different aspects of the general topic.

In Unit 1 we'll learn what the topic of statistics entails. We'll discuss some ways to collect the needed data for a statistical study. By the end the unit we'll have a view of how the two distinct divisions of statistics, descriptive and inferential, are related.

In Unit 2 we'll discover how to convert pure data into corrupted data, also referred to as ungrouped data into grouped data. Then we will examine some of the many ways data can be visually displayed graphically.

In Unit 3 we will examine ways to describe data by looking at its central tendency, its variation from its center, and how to determine the location of an element within a data set. A method of finding the proportions of variation a data set possesses will also be covered.

In Unit 4 we'll explore the basic concepts of probabilities, the branch of mathematics that allows us to take a sample and make predictions about the population from which it was derived. We'll strive to gain a fundamental understanding of probability through its addition, multiplication and counting rules.

In Unit 5 we combine the probability concepts and the statistical concepts we previously learned to construct discrete probability distributions. Then we'll learn how to find statistics of the distribution. The unit ends with a discussion on a specific discrete probability distribution called the binomial distribution.

In Unit 6 the discussion changes from discrete distributions to continuous random variable distributions. We begin looking at the Normal distribution and then quickly moving on the the Standard Normal distribution. We conclude the unit by learing how the Central Limit Theorem can be applied to sample data sets.

In Unit 7 we move into inferential statistcs. We learn how to use a sample mean to estimate the population mean, and how we can confidently report its value within a specific interval.

In Unit 8 we will examine the basics of hypothesis testing by using one-sample procedures for the hypothesis test of the population mean. In addition we will conclude our examination of topics in statistics by discussing the purpose of regression and correlation analysis. First, we'll examine some introductory terms, then focus on simple linear regression analysis and simple linear correlation analysis. During this final week of the course you will also complete the proctored Final Exam and the Course Evaluation.

Academic Honesty:
Academic integrity is the foundation of the academic community. Because each student has the primary responsibility for being academically honest, students are advised to read and understand all sections of this policy relating to standards of conduct and academic life.   Park University 2008-2009 Undergraduate Catalog Page 87
Academic dishonesty includes committing or the attempt to commit cheating, plagiarism, falsifying academic records, and other acts intentionally designed to provide unfair advantage to the students.

Cheating includes, but is not limited to, intentionally giving or receiving unauthorized aid or notes on examinations, papers, laboratory reports, exercises, projects, or class assignments which are intended to be individually completed.  Cheating also includes the unauthorized copying of tests or any other deceit or fraud related to the student's academic conduct.

Falsifying academic records includes, but is not limited to, altering grades or other academic records.

Other acts that constitute academic dishonesty include:

Stealing, manipulating, or interfering with an academic work of another student or faculty member.

Collusion with other students on work to be completed by one student.

Lying to or deceiving a faculty member.

Plagiarism:
Plagiarism involves the use of quotations without quotation marks, the use of quotations without indication of the source, the use of another's idea without acknowledging the source, the submission of a paper, laboratory report, project, or class assignment (any portion of such) prepared by another person, or incorrect paraphrasing. Park University 2008-2009 Undergraduate Catalog Page 87
ALL GRADED WORK FOR THIS COURSE MUST BE YOUR OWN.  EVERY QUIZ INSTRUCTION PAGE STATES THAT YOU ARE NOT TO RECEIVE OUTSIDE ASSISTANCE FROM ANYONE OTHER THAN YOUR INSTRUCTOR.  To further clarify; classmates, spouses, co-workers, tutors, clergy, librarians, friends, relatives, and pets are included as OUTSIDE ASSISTANCE.  PLEASE DO NOT VIOLATE THIS RULE.  WARNING: When I repeatedly see identical incorrect answers on quizzes I will be suspicious and will investigate.

When discussion questions request you to answer in your own words, do not copy words from the textbook as your own.  State YOUR understanding of the concept, not the understanding of some other person.  If you are allowed to quote the textbook, or other sources, you must use proper quotation markings and declare the source including web URL address or book page number from which you copied the text.  Not following these rules constitutes plagiarism, and will not be tolerated.  (This means you will not earn points for the assignment, and if the plagiarism does not stop immediately you will FAIL the course.  Additionally, a report of the incidence will be sent to your permanent academic file.)

Attendance Policy:
Instructors are required to maintain attendance records and to report absences via the online attendance reporting system.

  1. The instructor may excuse absences for valid reasons, but missed work must be made up within the semester/term of enrollment.
  2. Work missed through unexcused absences must also be made up within the semester/term of enrollment, but unexcused absences may carry further penalties.
  3. In the event of two consecutive weeks of unexcused absences in a semester/term of enrollment, the student will be administratively withdrawn, resulting in a grade of "F".
  4. A "Contract for Incomplete" will not be issued to a student who has unexcused or excessive absences recorded for a course.
  5. Students receiving Military Tuition Assistance or Veterans Administration educational benefits must not exceed three unexcused absences in the semester/term of enrollment. Excessive absences will be reported to the appropriate agency and may result in a monetary penalty to the student.
  6. Report of a "F" grade (attendance or academic) resulting from excessive absence for those students who are receiving financial assistance from agencies not mentioned in item 5 above will be reported to the appropriate agency.

Park University 2008-2009 Undergraduate Catalog Page 89-90

Disability Guidelines:
Park University is committed to meeting the needs of all students that meet the criteria for special assistance. These guidelines are designed to supply directions to students concerning the information necessary to accomplish this goal. It is Park University's policy to comply fully with federal and state law, including Section 504 of the Rehabilitation Act of 1973 and the Americans with Disabilities Act of 1990, regarding students with disabilities. In the case of any inconsistency between these guidelines and federal and/or state law, the provisions of the law will apply. Additional information concerning Park University's policies and procedures related to disability can be found on the Park University web page: http://www.park.edu/disability .



Rubric

CompetencyExceeds Expectation (3)Meets Expectation (2)Does Not Meet Expectation (1)No Evidence (0)
Evaluation                                                                                                                                                                                                                                                 
Outcomes
10                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                   
Can perform and interpret a hypothesis test with 100% accuracy. Can perform and interpret a hypothesis test with at least 80% accuracy. Can perform and interpret a hypothesis test with less than 80% accuracy. Makes no attempt to perform a test of hypothesis. 
Synthesis                                                                                                                                                                                                                                                  
Outcomes
10                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                   
Can compute and interpret a confidence interval for a sample mean for small and large samples, and for a proportion with 100% accuracy. Can compute and interpret a confidence interval for a sample mean for small and large samples, and for a proportion with at least 80% accuracy. Can compute and interpret a confidence interval for a sample mean for small and large samples, and for a proportion with less than 80%  accuracy. Makes no attempt to compute or interpret a confidence interval. 
Analysis                                                                                                                                                                                                                                                   
Outcomes
10                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                   
Can apply the normal distribution, Central limit theorem, and binomial distribution to practical problems with 100% accuracy. Can apply the normal distribution, Central limit theorem, and binomial distribution to practical problems with at least 80% accuracy. Can apply the normal distribution, Central limit theorem, and binomial distribution to practical problems with less than 80% accuracy. Makes no attempt to apply the normal distribution, Central Limit Theorem, or binomial distribution. 
Terminology                                                                                                                                                                                                                                                
Outcomes
4,5,7                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                
Can explain event, simple event, mutually exclusive events, independent events, discrete random variable, continuous random variable, sample,  and population with 100% accuracy. Can explain event, simple event, mutually exclusive events, independent events, discrete random variable, continuous random variable, sample,  and population with at least 80% accuracy. Can explain event, simple event, mutually exclusive events, independent events, discrete random variable, continuous random variable, sample,  and population with less than 80% accuracy. Makes no attempt to explain any of the terms listed. 
Concepts                                                                                                                                                                                                                                                   
Outcomes
1,6                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                  
Can explain mean, median, mode, standard deviation, simple probability, and measures of location with 100% accuracy. Can explain mean, median, mode, standard deviation, simple probability, and measures of location with at least 80% accuracy. Can explain mean, median, mode, standard deviation, simple probability, and measures of location with less than 80%  accuracy. Makes no attempt to define any concept. 
Application                                                                                                                                                                                                                                                
Outcomes
1,2,3,8,9                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                            
Compute probabilities using addition multiplication, and complement rules and conditional probabilities. Compute statistical quantities for raw and grouped data. Compute probabilities using combinatorics, discrete random variables, and continuous random variables. All must be done with 100% accuracy. Compute probabilities using addition multiplication, and complement rules and conditional probabilities. Compute statistical quantities for raw and grouped data. Compute probabilities using combinatorics, discrete random variables, and continuous random variables. All must be done with at least 80% accuracy. Compute probabilities using addition multiplication, and complement rules and conditional probabilities. Compute statistical quantities for raw and grouped data. Compute probabilities using combinatorics, discrete random variables, and continuous random variables. All are done with less than 80% accuracy. Makes no attempt to compute any of the probabilities or statistics listed. 
Whole Artifact                                                                                                                                                                                                                                             
Outcomes
7,8                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                  
Can apply the concepts of probability and statistics to real-world problems in other disciplines with 100 % accuracy. Can apply the concepts of probability and statistics to real-world problems in other disciplines with at least 80 % accuracy. Can apply the concepts of probability and statistics to real-world problems in other disciplines with less than 80% accuracy. Makes no attempt to apply the concepts to real-world problems. 
Components                                                                                                                                                                                                                                                 
Outcomes
1                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                    
Can use a calculator or other computing device to compute statistics with 100% accuracy. Can use a calculator or other computing device to compute statistics with at least 80% accuracy. Can use a calculator or other computing device to compute statistics with less 80% accuracy. Makes no attempt to use any computing device to compute statistics. 

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Last Updated:2/18/2009 1:57:37 PM